Triple

T15250628
Position Surface form Disambiguated ID Type / Status
Subject Meissen district E364508 entity
Predicate containsTown P847 FINISHED
Object Großenhain
Großenhain is a historic town in the Free State of Saxony in eastern Germany, known for its long-standing regional significance and traditional architecture.
E1170028 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Großenhain | Statement: [Meissen district, containsTown, Großenhain]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Großenhain
Context triple: [Meissen district, containsTown, Großenhain]
  • A. Ziegenhain
    Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
  • B. Treuenbrietzen
    Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
  • C. Ruppichteroth
    Ruppichteroth is a small municipality in western Germany’s North Rhine-Westphalia region, characterized by its rural setting and proximity to the metropolitan area of Cologne-Bonn.
  • D. Boltenhagen
    Boltenhagen is a Baltic Sea seaside resort town in northern Germany known for its beaches and tourism.
  • E. Geiersthal
    Geiersthal is a small municipality in the Bavarian Forest region of southeastern Germany.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Großenhain
Triple: [Meissen district, containsTown, Großenhain]
Generated description
Großenhain is a historic town in the Free State of Saxony in eastern Germany, known for its long-standing regional significance and traditional architecture.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Großenhain
Target entity description: Großenhain is a historic town in the Free State of Saxony in eastern Germany, known for its long-standing regional significance and traditional architecture.
  • A. Ziegenhain
    Ziegenhain is a historic town in the German state of Hesse, known for its medieval fortifications and role in regional conflicts.
  • B. Treuenbrietzen
    Treuenbrietzen is a historic town in the German state of Brandenburg, known for its medieval architecture and role in Reformation-era history.
  • C. Ruppichteroth
    Ruppichteroth is a small municipality in western Germany’s North Rhine-Westphalia region, characterized by its rural setting and proximity to the metropolitan area of Cologne-Bonn.
  • D. Boltenhagen
    Boltenhagen is a Baltic Sea seaside resort town in northern Germany known for its beaches and tourism.
  • E. Geiersthal
    Geiersthal is a small municipality in the Bavarian Forest region of southeastern Germany.
  • F. None of above. chosen

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007f62b9c8190b9ad40e2d1912b63 completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff677d34748190b5f723b5fd18b3a0 completed May 9, 2026, 4:57 p.m.
NEDg Description generation batch_69ff6856260c8190b82b40c484f87211 completed May 9, 2026, 5:01 p.m.
NED2 Entity disambiguation (via description) batch_69ff68e8e2c08190b460e23fe24f05e9 completed May 9, 2026, 5:03 p.m.
Created at: April 10, 2026, 3:13 a.m.